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This paper investigates the properties of DNA translocations signals in a stochastic framework. The considered
signals are relative to the translocation of single strand DNA through natural nanopores, and are obtained
using a planar patch clamp method. The stochastic signal analysis is carried out considering the statistical
distribution of DNA translocation parameters, considered as random variables including the amplitude, the
duration and the apparition of the DNA translocation events as well as the no-translocation signal features.
For each of these variables, a distribution function is proposed and assessed using a Kolmogorov-Smirnov
test, and their features are estimated. The DNA translocation signal stochastic analysis enables to characterize
the detection and/or estimation performances of existing algorithms, such as a breakdown detection algorithm,
in a stochastic framework. Moreover, it opens the way to the design of model based algorithms such as
detection tests using a likelihood ratio or joint detection-estimation algorithms using a maximum likelihood
approach, for an enhanced characterization of DNA translocations.
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